| Literature DB >> 32987123 |
Christian Tönnes1, Sonja Janssen2, Alena-Kathrin Golla3, Tanja Uhrig3, Khanlian Chung3, Lothar R Schad3, Frank Gerrit Zöllner3.
Abstract
Development of a deterministic algorithm for automated detection of the Arterial Input Function (AIF) in DCE-MRI of colorectal cancer. Using a filter pipeline to determine the AIF region of interest. Comparison to algorithms from literature with mean squared error and quantitative perfusion parameter Ktrans. The AIF found by our algorithm has a lower mean squared error (0.0022 ± 0.0021) in reference to the manual annotation than comparable algorithms. The error of Ktrans (21.52 ± 17.2%) is lower than that of other algorithms. Our algorithm generates reproducible results and thus supports a robust and comparable perfusion analysis.Entities:
Keywords: Arterial input function; Colorectal cancer; Dynamic contrast enhanced MRI; Quantitative perfusion; Segmentation
Year: 2020 PMID: 32987123 DOI: 10.1016/j.mri.2020.09.009
Source DB: PubMed Journal: Magn Reson Imaging ISSN: 0730-725X Impact factor: 2.546